This invention relates to a wireless communication method and a wireless communication apparatus for stable high-speed communication by using a plurality of transmission and receiver antennas, and more particularly, to a maximum likelihood decoding process for received signals.
A multiple-input multiple-output (MIMO) system in which wireless communication is performed by using a plurality of transmission and receiver antennas achieves a high transmission rate. However, in order to achieve a high transmission rate, it is necessary to accurately separate and detect interferences of a plurality of transmitted signals mixed in received signals therefrom. A maximum likelihood decoding (MLD) method can be used to obtain the most excellent property, but it cannot be free form large computational complexity because of its complicated process. Therefore, a QRM-MLD process has been proposed as a practical approximation process.
In “Performance Evaluation in Rayleigh Fading Environment using a Prototype MIMO-OFDM Transmission Equipment for a Millimeter-wave Mobile Camera”, Hiroyuki Furuta and Tetsuomi Ikeda, pp. 101-106, RCS2005-141, January 2006, Technical Report, Committee on radio communication systems, the Institute of Electronics, Information and Communication Engineers (IEICE) (hereinafter, referred to as “Non-Patent Document 1”), a technology is described in which inverse matrix calculation (zero-forcing) is performed in advance, the number of candidates for one transmitted signal is limited to a given number (for example, four), and all transmitted signals are estimated through the MLD process.
Further, JP 2006-211131 A describes a technology in which, after the inverse matrix calculation, described in Non-Patent Document 1, is performed, the number of candidates for each transmitted signal is set according to the signal-to-noise ratio of each of the transmitted signal, and all transmitted signals are estimated through the MLD process.
Referring to FIGS. 10 and 11, a conventional QRM-MLD process will be described.
FIG. 10 is a configuration diagram of a QRM-MLD process unit that executes the conventional QRM-MLD process.
The QRM-MLD process unit includes a channel estimator 71, a channel matrix generation unit 72, a QR decomposition process unit 73, a signal transform unit 74, and an MLD process unit 75.
The channel estimator 71 estimates a channel impulse response of each propagation channel by using pilot signals.
The channel matrix generation unit 72 generates a channel matrix H having the channel impulse responses estimated by the channel estimator 71, as matrix elements.
The QR decomposition process unit 73 applies QR decomposition to the channel matrix generated by the channel matrix generation unit 72. For example, when the number of transmitter antennas is four and the number of receiver antennas is four, the relationship between transmitted signals T and reception signals is R=HT expressed by the following formula.
                    Formula  1                                                                      [                                                                      r                  1                                                                                                      r                  2                                                                                                      r                  3                                                                                                      r                  4                                                              ]                =                              [                                                                                h                    11                                                                                        h                    12                                                                                        h                    13                                                                                        h                    14                                                                                                                    h                    21                                                                                        h                    22                                                                                        h                    23                                                                                        h                    24                                                                                                                    h                    31                                                                                        h                    32                                                                                        h                    33                                                                                        h                    34                                                                                                                    h                    41                                                                                        h                    42                                                                                        h                    43                                                                                        h                    44                                                                        ]                    ⁡                      [                                                                                t                    1                                                                                                                    t                    2                                                                                                                    t                    3                                                                                                                    t                    4                                                                        ]                                              (        1        )            
The QR decomposition applied to the channel matrix is H=QH′ expressed by the following formula.
                    Formula  2                                                                      [                                                                      h                  11                                                                              h                  12                                                                              h                  13                                                                              h                  14                                                                                                      h                  21                                                                              h                  22                                                                              h                  23                                                                              h                  24                                                                                                      h                  31                                                                              h                  32                                                                              h                  33                                                                              h                  34                                                                                                      h                  41                                                                              h                  42                                                                              h                  43                                                                              h                  44                                                              ]                =                              [                                                                                q                    11                                                                                        q                    12                                                                                        q                    13                                                                                        q                    14                                                                                                                    q                    21                                                                                        q                    22                                                                                        q                    23                                                                                        q                    24                                                                                                                    q                    31                                                                                        q                    32                                                                                        q                    33                                                                                        q                    34                                                                                                                    q                    41                                                                                        q                    42                                                                                        q                    43                                                                                        q                    44                                                                        ]                    ⁡                      [                                                                                h                    11                    ′                                                                                        h                    12                    ′                                                                                        h                    13                    ′                                                                                        h                    14                    ′                                                                                                0                                                                      h                    22                    ′                                                                                        h                    23                    ′                                                                                        h                    24                    ′                                                                                                0                                                  0                                                                      h                    33                    ′                                                                                        h                    34                    ′                                                                                                0                                                  0                                                  0                                                                      h                    44                    ′                                                                        ]                                              (        2        )            
The QR decomposition is a unique matrix transformation. A first matrix Q in the right side of the formula is a unitary matrix (where the matrix multiplication of the first matrix Q and the complex conjugate transposed matrix is equal to an identity matrix). A second matrix H′ in the right side of the formula is an upper triangular matrix.
Next, the complex conjugate transposed matrix of the matrix Q is expressed by Q*. When both sides of the formula (1) are multiplied by Q* from the left hand sides to obtain Q*R=Z in the left side of the formula, the right side of the formula is Q*HT=Q*(QH′)T=H′T expressed by the following formula.
                    Formula        ⁢                                  ⁢        3                                                                                  Q            *                    ⁡                      [                                                                                r                    1                                                                                                                    r                    2                                                                                                                    r                    3                                                                                                                    r                    4                                                                        ]                          =                              [                                                                                z                    1                                                                                                                    z                    2                                                                                                                    z                    3                                                                                                                    z                    4                                                                        ]                    =                                    [                                                                                          h                      11                      ′                                                                                                  h                      12                      ′                                                                                                  h                      13                      ′                                                                                                  h                      14                      ′                                                                                                            0                                                                              h                      22                      ′                                                                                                  h                      23                      ′                                                                                                  h                      24                      ′                                                                                                            0                                                        0                                                                              h                      33                      ′                                                                                                  h                      34                      ′                                                                                                            0                                                        0                                                        0                                                                              h                      44                      ′                                                                                  ]                        ⁡                          [                                                                                          t                      1                                                                                                                                  t                      2                                                                                                                                  t                      3                                                                                                                                  t                      4                                                                                  ]                                                          (        3        )            
The signal transform unit 74 multiplies received signals by the complex conjugate transposed matrix of the unitary matrix, obtained through the QR decomposition, to transform the received signals into new signals. For example, the signal transform unit 74 multiplies a received-signal matrix R by the complex conjugate transposed matrix Q* to transform the received-signal matrix R to a signal matrix Z, as expressed by the formula (3).
The MLD process unit 75 estimates transmitted signals through an MLD process.
Next, details of the MLD process performed after the QR decomposition will be described. When t4 is focused on in the formula (3), z4=h44′t4 is established. When a QPSK system is used for modulation and demodulation, four types of symbol replica candidates for a transmitted signal are obtained corresponding to the number of levels. For each of the symbol candidates, “h44′t4” is calculated and the squared Euclidean distance from z4 is calculated. It is estimated that the symbol candidate having the shortest Euclidean distance, among the calculated Euclidean distances, is most likely to be a proper transmitted signal. Next, when focusing on t3, z3=h33′t3+h34′t4 is established. Therefore, for each of the combinations (4×4=16 types) of symbol candidates for t3 and t4, “h33′t3+h34′t4” is calculated and the squared Euclidean distance from z3 is calculated. The Euclidean distance for each of 16 types of symbol candidates is calculated by combining the squared Euclidean distance from z3 and the squared Euclidean distance from z4. It is estimated that the symbol candidate having the shortest Euclidean distance, among the calculated Euclidean distances, is most likely to be a proper signal. The similar processing is repeated up to t1 in the MLD process. It should be noted that distance calculation is required for 256 (fourth power of four) types of symbol candidates for t1, and in general, when symbols of C levels are sent by N transmitter antennas, the computational complexity as large as the Nth power of C is required. In order to reduce the computational complexity, an M-algorithm is used.
FIG. 11 is an operation diagram of a process of a conventional M-algorithm.
First, four types of symbol replicas C1 to C4 are created as candidates for the transmitted signal t4. A symbol replica is a signal temporarily set in a receiver. Specifically, the symbol replica is a signal assumed to be a received signal based on an estimated channel impulse response.
Next, for each of the four types of symbol replicas C1 to C4, four types of candidates for the transmitted signal t3 are created as symbol replicas, to set 16 types of candidates for the combination of (t3, t4). Then, the squared Euclidean distances between each of the set transmitted signal candidates and a transformation signal Z are calculated, and combinations of (t3, t4) are narrowed down in an ascending order of the calculated squared Euclidean distances. For example, in a case where M=3 as shown in FIG. 11, combinations of (t3, t4) are narrowed down to three candidates.
Next, for the three transmitted signal candidates, obtained by narrowing down the combinations of (t3, t4) for the transmitted signal t3, four types of symbol replicas for the transmitted signal t2 are created, to set 12 types of candidates for the combination of (t2, t3, t4). Then the squared Euclidean distances between each of the set transmission signal candidates and a convension signal Z are calculated and combinations of (t2, t3, t4) are narrowed down (M=3) in an ascending order of the calculated squared Euclidean distances.
Finally, for the transmitted signal t1, the process of the M-algorithm is also applied to three transmitted signal candidates obtained by narrowing down combinations of (t2, t3, t4) for the transmitted signal t2, to finally determine the combination of (t1, t2, t3, t4) having the shortest squared Euclidean distance. In short, when combinations of candidates are narrowed down during the process, an optimum solution may be missed, but an exponential increase in computational complexity can be suppressed.